A data warehouse is a repository for historical data, which allows analysts to evaluate multiple data sources in order to get actionable information. A data warehouse can be deployed on the premises or in the cloud. The choice you make is contingent on your business’s requirements and factors such as cost and scalability, security, control and resources.
Data warehouses are designed to store large amounts of historical enterprise data as well as performing in-depth data analysis for business intelligence and reporting (BI). They can store relational and non-relational data. They are usually structured, meaning the data is extracted, loaded and transformed (ELT) to meet pre-defined schemas before it is stored, which allows you to run queries against them much easier than executing them directly against source systems that are operational.
Traditional data warehouses on premises need expensive hardware and software to host them. Their storage capacity is limited to their compute and they have to constantly delete older data in order to keep enough space to store current data. A data warehouse enables you to run queries that are based on historical data which are not possible on operational systems as they only update with real-time data.
A cloud-based, data store or managed service, is fully automated and a highly efficient solution. It is a great option for companies that require the analysis of large quantities of data over the long run. It is usually a more cost-effective alternative to traditional data warehouses, since it doesn’t require you to have large servers and provides flexible pricing. You can pay per the hour or throughput, or a fixed amount of resources.